log_comp_dens_conv

data


compute the log density of the components of the
    mixture m when convoluted with a normal with standard deviation
    s or a scaled (se) student.t with df v, the density is
    evaluated at x


The R package 'ashr' implements an Empirical Bayes approach for large-scale hypothesis testing and false discovery rate (FDR) estimation based on the methods proposed in M. Stephens, 2016, "False discovery rates: a new deal", <DOI:10.1093/biostatistics/kxw041>. These methods can be applied whenever two sets of summary statistics---estimated effects and standard errors---are available, just as 'qvalue' can be applied to previously computed p-values. Two main interfaces are provided: ash(), which is more user-friendly; and ash.workhorse(), which has more options and is geared toward advanced users.

log_comp_dens_conv: log_comp_dens_conv

Description

Usage

Arguments

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